Ab initio informed solute drag assessment for ferritic steels

Abstract

Linking atomistic information on solute interactions with microstructure evolution is a key challenge for predictive modelling of chemistry effects on material properties. The objective of the present work is to provide a link between grain boundary segregation energies with GB migration kinetics on the example of recrystallization in multi-component ferritic steels. For that purpose, the segregation of 64 elements from the periodic table to a representative grain boundary is computed with ab initio density functional theory. To connect this data to grain boundary migration kinetics, the solute trend parameter from a simplified solute drag treatment is employed. The solute trend parameter for individual solutes is presented, which highlights solutes with large impact on grain boundary migration. Furthermore, an extension of the solute trend parameter is introduced that allows to evaluate the solute drag potential of realistic steel compositions. The necessity to include solute co-segregation, site competition, and precipitation effects is shown in a comparison to experimental data on recrystallization kinetics. The comparison to experimental data demonstrates the qualitative predictability of recrystallization kinetics by the extended solute trend parameter.